Challenges of Solar Cycle Prediction Introduced by Rogue Active - PowerPoint PPT Presentation

Challenges of Solar Cycle Prediction Introduced by ’Rogue’ Active Region Emergences and Meridional Inflow Melinda Nagy 1 au 2 Paul l Char arbonneau rle 3 Alexan andre Lemerle Kristóf Petrovay 1 1 1 Eötvös Loránd University, Budapest, Hungary 2 2 Université de Montréal 3 Collège de Bois-de-Boulogne, Montréal

Challe llenges es of predic ictio ion 1. Rogue BMRs One single ‘rogue’ BMR, as it can have a flux content commensurate to the maximum of the polar cap flux, has a huge impact on the subsequent cycle. Due to this fact, it is very important to treat these extreme events in prediction. 2. Meridional inflow Potential non-linear mechanism 3. Torsional oscillation – next step Melinda Nagy 2

The kinematic „2 × 2D” Babcock-Leighton dynamo model Lemerle et al., 2015, ApJ 801; Lemerle & Charbonneau, 2017, ApJ 834 Flux Transport Dynamo Surface Flux Transport FTD (2D) SFT (2D) Emergence of new BMRs Flux, tilt, separation, etc. chosen randomly based on corresponding distribution functions of cycle 21 ( + tilt scatter! ) Melinda Nagy 3

Solar-like Solution Dipole moment is a good precursor of cycle amplitude: Svalgaardet al., 2005, GRL, 32, L01104 Melinda Nagy 4

Solar-like Solution - prediction ‚rogue’ BMR – unusually strong flux, and high tilt angle → big contribution to the dipole moment Initial contribution to the dipole moment Flux of the latitude trailing polarity tilt angle separation Melinda Nagy 5

Solar-like Solution - prediction Melinda Nagy 6

Meridional inflow → flow perturbation • The inflows are caused by flows towards individual active regions due to the local cooling effect of the magnetic field . • Surface effect, decreases quickly with depth. • According to measurements, the inflow strength is about 3-5 m/s on average H. C. Spruit 2003 SoPh 213 Model of inflows towards an activity complex formed by several emerged BMRs. The colour scale encodes the strength of the magnetic field B r . D. Martin-Beldaand R. H. Cameron 2017 A&A 597 Melinda Nagy 7

Meridional inflow → flow perturbation Helioseismic measurements of the meridional flow during cycle 23: the perturbation caused by the inflows is the strongest at cycle maximum. I. Gonzalez Hernandezet al. 2010 ApJ 713 The inflows represent a potential non-linear mechanism capable of limiting the build up of the polar fields and contributing to the modulation of the solar cycle . R. H. Cameron and M. Schüssler 2010 ApJ 720 Melinda Nagy 8

Models of the meridional inflow J. Jiang et al. 2010 ApJ 717 Perturbation in the meridional flow in their Surface Flux Transport model. The inflow belt moves together with the activity belt, fix width and flowspeed. Result: reduction of polar fields by ~18% Melinda Nagy 9

Models of the meridional inflow J. Jiang et al. 2010 ApJ 717 Perturbation in the meridional flow in their Surface Flux Transport model. The inflow belt moves together with the activity belt, fix width and flowspeed. Result: reduction of polar fields by ~18% R. H. Cameron and M. Schüssler 2010 ApJ 720 Magnetic field dependent flow speed.  The flow should depend on the strength of the cycle. Melinda Nagy 10

Meridional inflow in the 2×2D model J. Jiang et al. 2010 ApJ 717 Based on the concept of Jiang et al. , BUT: • Flow parameters defined with the parameters of the emerged active regions. • Calculated separately for the two hemispheres – asymmetry • Updated at each internal dynamo timestep Melinda Nagy 11

Meridional inflow in the 2×2D model Flow velocity v 00 = 5 m/s – observations (5.25 m/s; 5.50 m/s; 7.50 m/s) F 00 = 4.99 10 21 Mx (average unsigned flux) F i – flux of BMRs emerged during an internal dynamo timestep Flux-weighted centroidof the inflow belt  i – midpoints of BMRs Width of the inflow belt n – number of emerged BMRs on the North / South Melinda Nagy 12

Preliminary results 13 Melinda Nagy

Reduced stochasticity Full stochasticity (tilt angle varies according to Joy’s law; non- stochastic separation) No inflow Inflow (v 00 = 7.5 m/s) Melinda Nagy 14

Reduced stochasticity Full stochasticity (tilt angle varies according to Joy’s law; non- stochastic separation) No inflow Inflow  SSN max = 17%  D max = 10%  SSN max = 19%  D max = 12% (v 00 = 7.5 m/s) Melinda Nagy 15

Conclusions Flux dependent meridional inflow is added to the 2×2D Babcock-Leighton solar dynamo model. Results: - The inflow reduces the dipole moment by ~10% → reduction in the cycle amplitudes, too ( cycle prediction! ) - Cross-equatorial flows → stronger hemispheric coupling ( asymmetry! ) Next step: - Link cross-equatorial flows to hemispheric asymmetry - More case studies to investigate the impact of meridional inflows on cycles with different amplitude (different effects are proposed) Melinda Nagy 16

Thank you for your attention! Acknowledgement : This research is supported by the ÚNKP-18-3 New National Excellence Program of the Ministry of Human Capacitiesand by the Hungarian National Research, Development and Innovation Office (NKFI grant no. K128384). 17

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Case se studie ies Melinda Nagy 19

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Preliminary results – shape of the inflow  v > 0 – flow towards the South  v < 0 – flow towards the North Melinda Nagy 22

Models of the meridional inflow R. H. Cameron and M. Schüssler 2012 A&A 548 Cross-equatorial flows: • BMRs close to the equator: enhanced flux transport between hemispheres -> it strengthens the dipole moment (in case of weak cycles) • In general: converging flows decrease the tilt angle of the BMRs -> lower contribution to the dipole moment (in case of strong cycles, where the activity belts are further from the equator, this effect will weaken the dipole moment ) Nonlinear feedback! Melinda Nagy 23

Reduced stochasticity Full stochasticity (tilt angle varies according to Joy’s law; non-stochastic separation) No inflow Hemispheric Asymmetry Inflow Asymmetry of a cycle can be predicted (v 00 = 7.5 with polar field asymmetry of the m/s) Preceding cycle. Note: rogue BMRs have impact on hemispheris asymmetry! Melinda Nagy 24

Full simulation with flux dependent inflow and stochastic tilt & separation. - Cycle-to-cycle variation - Hemispheric asymmetry - Cross-hemispheric flows Melinda Nagy 25

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Method Me   Lead  Trail  D BMR F Trail [10 23 Mx] Date d -0.2210*10 23 2175.68 84.80 89.50 -8.54 31.65 2.43 Melinda Nagy 27